diff --git a/docs/quickstart/installation.md b/docs/quickstart/installation.md
index 2a2db44534..950aefb2a0 100644
--- a/docs/quickstart/installation.md
+++ b/docs/quickstart/installation.md
@@ -140,7 +140,7 @@ To restrict to only CUDA architectures that you have available locally, use the
 build arg and look up [the compute capability for your GPU](https://developer.nvidia.com/cuda-gpus).
 For example, here's how to build with support for GeForce 30xx series GPUs:
 ```bash
-docker build --build-arg CUDA_ARCHITECTURES=86 -tag nerfstudio-86 .
+docker build --build-arg CUDA_ARCHITECTURES=86 --tag nerfstudio-86 -f Dockerfile .
 ```
 
 ### Using an interactive container
diff --git a/nerfstudio/data/dataparsers/scannet_dataparser.py b/nerfstudio/data/dataparsers/scannet_dataparser.py
index 3a58f302a7..46ff98f8a8 100644
--- a/nerfstudio/data/dataparsers/scannet_dataparser.py
+++ b/nerfstudio/data/dataparsers/scannet_dataparser.py
@@ -82,9 +82,9 @@ def _generate_dataparser_outputs(self, split="train"):
         K = np.loadtxt(self.config.data / "intrinsic" / "intrinsic_color.txt")
         for img, depth, pose in zip(img_dir_sorted, depth_dir_sorted, pose_dir_sorted):
             pose = np.loadtxt(pose)
-            frame_pose[0:3, 1:3] *= -1
-            frame_pose = frame_pose[np.array([1, 0, 2, 3]), :]
-            frame_pose[2, :] *= -1
+            pose[0:3, 1:3] *= -1
+            pose = pose[np.array([1, 0, 2, 3]), :]
+            pose[2, :] *= -1
 
             # We cannot accept files directly, as some of the poses are invalid
             if np.isinf(pose).any():